Connectionist Temporal Classification [1]} is a segmentation-free and alignment-free algorithm that provides a trainable loss for sequence-to-sequence transduction. It is widely used in Automatic Speech Recognition and Handwritten Text Recognition [2]}, [3]}, [4]} where the goal is to convert a sequence of audio or visual features respectively into a set of target units.
